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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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computational analysis of functional genomics datasets with an emphasis on single-cell omics. This person will develop new computational methods to analyze novel RNAseq, ATACseq, and Spatial Transcriptomics
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Engineering at Harvard University seeks outstanding postdoctoral applicants with expertise in non-human primate immunology and virology or analysis of spatial omics data to join an interdisciplinary team
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on understanding the earliest stages of high-grade serous ovarian cancer (HGSOC) by integrating spatial multi-omic profiling with computational analysis to define how precancerous lesions evolve into invasive
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We